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atelier-mcp

atelier-mcp

by anshrajore
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Remote

critique_backend

Audit backend and pipeline code against OWASP security, 12-factor principles, N+1 query issues, input validation, and zero-orphan workflow nodes.

Instructions

Audit backend and pipeline code against OWASP security, 12-factor principles, N+1 query elimination, input boundary validation, and zero-orphan workflow node rules.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "code": "<code>"
    },
    "name": "critique_backend"
  }
}

Input Schema

NameRequiredDescriptionDefault
codeYesThe backend endpoint, service logic, or workflow orchestration JSON (e.g. n8n, LangGraph).
filePathNoOptional path of the backend file or workflow graph.
languageNoProgramming language of the code snippet.
frameworkNoBackend framework or workflow orchestrator.
isWorkflowJsonNoSet to true if evaluating an orchestration graph JSON payload.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.2

TDQS

C2.9/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full behavioral burden. It does not state whether the audit is read-only, requires network/database access, authenticates to external services, has rate limits, or what kind of output (scores, findings, severity levels) is returned. It also doesn't clarify whether findings are deterministic or LLM-judgment based.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

A single, front-loaded sentence that lists the audit dimensions without filler. It is efficient, though the long enumeration could be structured as a list for readability.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description covers the audit dimensions and the schema covers all parameters, but with no annotations and no output schema, it omits important context: what the tool returns (findings format, severity), whether it mutates anything, and when to choose it over critique_ui. Adequate but with clear gaps for a multi-parameter audit tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents code, filePath, language, framework, and isWorkflowJson fully. The description adds no syntax, format, or usage guidance beyond what the schema provides, so the baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb (audit) and resource (backend and pipeline code), and it enumerates the rule sets checked (OWASP, 12-factor, N+1, input boundary validation, zero-orphan workflow nodes). It is clear about what the tool does, though it does not distinguish itself from critique_ui or explain the relationship to generate_fix.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is no explicit when-to-use guidance, prerequisites, or alternatives named. The agent must infer that this tool is for backend code while critique_ui handles UI, and that generate_fix is separate.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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